The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Voi. XXXVII. Part B7. Beijing 2008
1308
Figure 1. Location of the study area Tegucigalpa in Honduras.
Source
Date
Format
Resolution
Quickbird
12/2000
Raster
ms: 2.4 m;
pan: 0.61 m
ResourceSat P-6
04/2006
Raster
5.8 m
Aerial Photographs
2001
Raster
0.4 m
DTM
n.a.
Vector
1.5 m
Lidar nDSM
03/2000
Raster
1 m
Hazard maps (floods
& landslides)
2002
Vector
1:10 000
Main river network
2000
Vector
1:10 000
Various
infrastructure
2002 &
2004
Vector
n.a.
Table 1. Data base available for the analysis.
3. SOCIAL VULNERABILITY - DEFINITION AND
ASSESSMENT
This paper deals with the assessment of social vulnerability, one
component of risk that has frequently been neglected in this
context. Not only because no consensus on its definition has
been found yet, but also because existing assessment
approaches are rather time and/or cost intensive.
We follow Clark et al. (1998) in defining SV as “people's
differential incapacity to deal with hazards, based on the
position of the groups and individuals within both the physical
and social worlds", which has to be assessed with respect to the
particular hazard or combination thereof (e.g. earthquakes
and/or landslides). SV cannot be expressed in absolute values or
losses. To quantify SV and to make it comparable between
regions, indices containing different variables have been
developed (Cutter et al., 2003), which are in most cases derived
from data collected during community-based approaches or
from census data.
While data collected using house-to-house surveys, community-
based methods (Kienberger & Steinbruch, 2005) and house-to-
house surveys (Palmiano-Reganit, 2005) are suitably detailed,
only small areas can be covered. The method is also time-
consuming, of low temporal resolution, and up-scalability of the
results is questionable. On the other hand, census data based
approaches (Cutter et al., 2003, Azar & Rain, 2007) are less
time and cost intensive, but have a lower spatial resolution and
can due to data availability only be repeated every 5 to 10 years.
It has to be considered that SV is not only spatially, but also
temporally highly dynamic. The main limitation, however, is
that census data are collected for other purposes and that
important components of SV, such as hazard perception, are not
included.
Individual or small group af individuals
individual and household related
indicators far social vulnerability
- age & gender
\ - me c & ethnic i tv
- employment $tatus
- literacy
- household si/e
I - tenure statu»
- access to water, gas and power supply & waste disposal
( * social standard
- knowledge about Iwtzard & risk
- access to information
* willingness to decrease susceptibility
- residence type
- building stock
* building construction material
proximity to hazard zone
* relief slope (depends on purpose of indicator)
- abundance of transport in fro ¡structure
~ road conditions
- building density proportion of built-up area
- roof material and roof size
distance to neighbouring building
st/.c and distribution of green «paces
- commercial and industrial development
- distance to city centre, rural urban
- supply with gas. water and electricity
I - abundance of education fact lilies
U abundance of medical facilities
U abundance of emergency management
I- building codes Iff;
Figure 2. Indicators for social vulnerability assessment on individual/household and neighbourhood level and their proposed
assessment methods.
A supplementary cost- and time-efficient approach that can be
repeated frequently and that can be used in combination with
traditional methods is thus needed. Satellite data have
previously shown their high potential for the application in risk-
related topics and with the arrival of high resolution satellite
sensors, enhanced image quality, and new image processing
methodologies, a continuously growing number of information
can be delineated from remote sensing data, particularly in
